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研究生:蔡佩珊
研究生(外文):Peishan Tsai
論文名稱:應用類神經網路支援天然瓦斯需求之研究
指導教授:洪新原洪新原引用關係
學位類別:碩士
校院名稱:國立中正大學
系所名稱:資訊管理學系
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2001
畢業學年度:89
語文別:中文
論文頁數:116
中文關鍵詞:類神經網路複迴歸人工智慧需求預測
外文關鍵詞:Artificial Neural NetworksMultiple RegressionArtificial IntelligenceDemand Forecasting
相關次數:
  • 被引用被引用:9
  • 點閱點閱:227
  • 評分評分:
  • 下載下載:44
  • 收藏至我的研究室書目清單書目收藏:1
近年來,由於美國政府發佈對天然瓦斯工業的撤銷管制,引起許多企業紛紛投入此一產業,由於產業競爭程度的加劇,如何準確的預測天然瓦斯需求量以降低營運成本,也就成為一項重要的工作。本研究參考Hodges et al.(1997)所做的研究,運用與Hodges et al.(1997)相同的資料集,並考慮其在統計上複迴歸的限制,包括:自變數與相依變數必須為直線關係、誤差項的變異數必須相等、誤差項的獨立性、以及必須為常態分配等基本假設。然而,應用以類神經網路為基礎的方法,則無上述這些基本假設的限制,因此是一個可行的替代工具。
本研究之主要問題有四:(1)檢測Hodges et al.(1997)所採用的Odessa資料集是否適用複迴歸;(2)找出具有良好預測能力的類神經網路模式;(3)驗證類神經網路預測模式的績效;(4)討論此預測模組的概化能力。本研究運用統計檢定方法,對資料集進行檢驗,以求證資料集是否符合統計的假設。研究結果顯示,應變數與自變數並非直線關係、誤差項的變異數不相等、並非常態分配、而且有離群值與共線性的現象。另外,本研究採用類神經網路,針對相同的資料集來進行訓練,試圖找出更為優良的網路模組來支援天然瓦斯的需求預測。研究結果發現類神經網路的預測能力,可以優於統計複迴歸方法,可以提供了更為準確的需求預測。
Since the Federal Government of the United States has deregulated the interstate natural gas industry, many cities intervene to take over the supply and transmission functions. Accordingly, an accurate forecasting model of gas demand is critical for the efficient operation. In this research, artificial neural networks (ANN) technology is applied to develop such a model.
We first test basic assumptions behind the multiple regression technique, which was used by Hodges et al. (1997), to examine its fitness. Second, we develop an effective forecasting model using artificial neural networks. Third, the ANN-based forecasting model is empirically tested. Finally, we discuss the generalizability of the ANN-based forecasting model. The implications from the findings are also provided.
第一節 緒論1
第一節 研究背景與動機1
第二節 研究目的與問題3
第三節 研究貢獻5
第四節 研究流程6
第二節 文獻探討7
第一節 天然瓦斯需求預測之相關研究7
第二節 關於複迴歸分析與限制10
第三節 類神經網路之介紹12
第四節 類神經網路的應用21
第三節 研究方法26
第一節 重新檢示HODGES ET AL.(1997)所建構之天然瓦斯需求預測之複迴歸需求預測模組26
第二節 建立天然瓦斯需求之預測模組架構28
第三節 預測績效模組之建立32
第四節 概化能力34
第四節 研究成果36
第一節 檢測複迴歸假設36
第二節 類神經網路績效之比較41
第三節 概化能力54
第四節 樣本數的增加是否提高預測能力87
第五節 結論及未來研究方向95
第一節 研究結論95
第二節 研究限制98
第三節 未來方向98
第四節 總結99
中文部分
1.胡玉城,暢談類神經網路,倚天資訊股份有限公司,民國81年1月。
2.林家弘,以類神經網路為基礎的輔助醫師開要系統之探討,國立中正大學資訊管理研究所碩士論文,民國87年6月。
3.黃俊英,多變量分析,中國經濟企業研究所,民國84年6月。
4.葉怡成,類神經網路模式應用與實作,儒林圖書有限公司,民國83年9月。
5.範俊波、譚永冬,神經網路與神經計算機,儒林圖書有限公司。民國81年10月。
6.林家賢,類神經網路在結構分析上的應用,國立中正大學機械工程研究所碩士論文,民國82年6月。
7.林威廷,以總體經濟因素預測股票報酬率─類神經網路與多元迴歸之比較研,國立交通大學資訊管理研究所碩士論文,民國84年6月。
8.中時蕃薯藤電子報,http://ctnews.yam.com.tw/news/200101/26/97571.html,民國90年1月27日。
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